Presence/Absence maps of phytoplankton in the Greater North Sea | Emodnet Biology

Presence/Absence maps of phytoplankton in the Greater North Sea

EMODnet Biology phytoplankton of the Greater North Sea

The project aims to produce comprehensive data products of the occurrence and absence of (phyto)plankton species. As a basis, data from EMODnet Biology are used. The selection of relevant datasets is optimized in order to find all planktonic species, and exclude all species that are not planktonic. The occurrences from EMODnet Biology were complemented with absence data assuming fixed species lists within each dataset and year. The products are presented as maps of the distribution of the 100 most common species of (phyto)plankton in the Greater North Sea.

This product then is also used for interpolated maps, using the DIVA software (Barth et al., 2014, 2020)

Geographical coverage

The aim is to cover the Greater North Sea. Subareas from the layer intersect of the Exclusive Economic Zones and IHO sea areas in marineregions.org (Flanders Marine Institute, 2020) were selected as in the map below. Kattegat and Skagerrak were excluded for the moment, but could be added in a later stage.

Map of regions

The regions were selected by manual procedure in QGIS from the GIS layer "MarineRegions:eez_iho" available via WFS via the EMODnet Biology geoserver. The selection was saved as GeoJSON in the project at "data/derived_data/simplified_greater_north_sea-selection_from_eez-iho_v4.geojson"

Temporal coverage

All available data from 1995 to current (2020-05-31) were used in this product.

Directory structure

EMODnet-Biology-Phytoplankton-Greater-NorthSea/
    ├── analysis
    ├── data/
    │   ├── derived_data/
    │   └── raw_data/
    ├── docs/
    ├── product/
    └── scripts/
  • analysis - Markdown
  • data - Raw and derived data
  • docs - Rendered reports
  • product - Output product files
  • scripts - Reusable code

Data series

Raw data were downloaded from EMODnet Biology using WFS requests. This was done in two steps.

  1. For each subregion, all observations of species with the trait "phytoplankton" or "Phytoplankton" were extracted.
  2. Because of uncertainties in extracting all phytoplankton species (due to absence of traits for example) all data was extracted for every dataset that occurred in step 1. Because datasets could also contain non-phytoplankton, within the datasets phyla were selected that contain phytoplankton species, after which a manual selection was performed to filter out non-phytoplankton species also belonging to these phyla (e.g. macroalgae).

The datasets included were:

Dataset EMODnet Biology link
Continuous Plankton Recorder (Phytoplankton) https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=785
NODC World Ocean Database 2001: Plankton Data https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=1985
REPHY: Network Monitoring phytoplankton https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=2451
ICES Phytoplankton Community dataset https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=4424
AMOREII: Advanced Modelling and Research on Eutrophication Linking Eutrophication and Biological Resources (AMOREII) https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=5977
AMOREIII: Combined Effect of Changing Hydroclimate and Human Activity on Coastal Ecosystem Health (AMOREIII) https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=5978
Phytoplankton Monitoring at the Château du Taureau Station in the Western English Channel, from 2009 to 2011 https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=5998
Long-term Monitoring of the Phytoplankton at the SOMLIT-Astan Station in the Western English Channel from 2000 to Present https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=5971
LifeWatch observatory data: phytoplankton observations by imaging flow cytometry (FlowCam) in the Belgian Part of the North Sea https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=4688
Biogeographic data from BODC - British Oceanographic Data Centre https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=1172
DASSH: The UK Archive for Marine Species and Habitats Data https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=5247
L4 Plankton Monitoring Programme https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=1495
Phytoplankton data for Danish marine monitoring (ODAM) from 1988 - 2016 https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=5664
Dutch long term monitoring of phytoplankton in the Dutch Continental Economical Zone of the North Sea https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=5758
PANGAEA - Data from various sources https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=2722
PANGAEA - Data from Ocean margin exchange project (OMEX I) https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=2768
Macrobenthos and Phytoplankton monitoring in the Belgian coastal zone in the context of the EU Water Framework Directive (WFD) https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=5945
IPMS-PHAEO: Dynamics of coastal eutrophicated ecosystems https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=5951
AMORE: Advanced Modelling & Research on Eutrophication & the Structure of Coastal Planktonic Food-webs: Mechanisms & Modelling (AMORE) https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=5976

 

WFS requests are described in the script "requestData.R"

Data product

Addition of zero values

Within each combination of dataset and year, it was assumed that the potentially occurring species did not vary. For example, if a species was found within a dataset in March at a certain location, it was assumed that this species was always searched for. If in the same dataset, but at another location or at another time, this same species was not reported, it was assumed to be absent. This approach allows for variation in e.g. counting strategy or analyzing lab between years, where perhaps certain species were not looked for in a certain period.

For the 100 most abundant species this analysis was done, after which maps were produced with the probability of occurrence of a certain species according to the fraction of presences divided by the total sampling effort (number of samples taken). The analyses was done an a course grid and a finer grid, for each season (winter, spring, summer, autumn)

More information

References

Barth, A., Beckers, J.-M., Troupin, C., Alvera-Azcárate, A., and Vandenbulcke, L.(2014): divand-1.0: n-dimensional variational data analysis for ocean observations, Geosci. Model Dev., 7, 225–241, https://doi.org/10.5194/gmd-7-225-2014.

Barth, A., Stolte, W., Troupin, C. & van der Heijden, L. (2020). Probability maps for different phytoplankton species in the North Sea. Integrated data products created under the European Marine Observation Data Network (EMODnet) Biology project (EASME/EMFF/2017/1.3.1.2/02/SI2.789013), funded by the by the European Union under Regulation (EU) No 508/2014 of the European Parliament and of the Council of 15 May 2014 on the European Maritime and Fisheries Fund. Available online at https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=6588

Flanders Marine Institute (2020). The intersect of the Exclusive Economic Zones and IHO sea areas, version 4. Available online at https://www.marineregions.org/.https://doi.org/10.14284/402

Code and methodology

All code is available on github at: https://github.com/EMODnet/EMODnet-Biology-Phytoplankton-Greater-NorthSea

Citation and download link

Please cite this product as:

Stolte, W. & van der Heijden, L. (2020). Presence/Absence maps of phytoplankton in the Greater North Sea. Integrated data products created under the European Marine Observation Data Network (EMODnet) Biology project (EASME/EMFF/2017/1.3.1.2/02/SI2.789013), funded by the by the European Union under Regulation (EU) No 508/2014 of the European Parliament and of the Council of 15 May 2014 on the European Maritime and Fisheries Fund

Available to download in:

https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=6587

This link downloads a zip file containing a local copy of this git repository with the data products in the ./product/ subdirectory. The scripts and workflows included in this local git repository may differ from the pipelines included in this remote repository on GitHub as we continue to improve the product. To see the differences between the local copy of the git repository you downloaded and the latest version on GitHub, open the git bash console and type:

$ git fetch origin master
$ git diff origin/master

If you want to update the local copy of the git repository you downloaded to the latest development version, run the following line:

$ git pull

If you are unsure about how to use git, please check the installation guide of the git book: https://git-scm.com/book

Authors

Willem Stolte and Luuk van der Heijden.

 

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